In a March 2016 article published in The Hill, David Leduc and Hudson Hollister argue that fraud schemes such as Bernie Madoff’s elaborate Ponzi scheme could have been prevented if financial reporting data had been more widely shared and searchable across multiple offices at the Securities and Exchange Commission (SEC). They argue that Madoff’s deception went undetected for so long because of a data failure.
“The lack of open, searchable data hurts the agencies’ missions. It makes data analytics cumbersome and expensive. It allows frauds like Madoff’s to go undetected,” the article states.
Nearly a decade after Madoff’s conviction, the Holy Grail of financial secure data sharing remains a work in progress. Much of the progress can be traced to programs like Lerner’s Ph.D. in financial services analytics (FSAN). Courses like FINC843/FSAN843, Financial Services Regulation, explore how big data insights can be balanced with reasonable market regulation.
In a paper titled Financial Services Technology 2020 and Beyond: Embracing disruption, PricewaterhouseCoopers global financial service technology leader Julien Courbe explains that “regulators can compare scenarios and address potential issues before they become full-scale market problems” through the use of “sophisticated analytical tools on large volumes of data.”
The paper gives a few examples in the United States:
- The SEC’s Office of Compliance Inspections and Examinations (OCIE) has invested significant resources to enhance its data mining and analysis capabilities, such as its National Exam Analytics Tool, or NEAT, which combs through data to identify potential insider trading, improper allocation of investment opportunities and other infractions.
- The Consumer Financial Protection Bureau (CFPB), which focuses on consumer protection, has invested heavily in analytics and digital technology, such as its creation of eRegulations, an online tool to help users find, research, and understand regulations.
- CFPB has also developed Project Qu, an open source data platform that lets users query complex data about mortgage loans, combine it with other data and then summarize it.
With a new presidential administration starting the process for changing several regulations, including elements of the Dodd-Frank legislation, much of the future of financial regulation remains unresolved.
Regardless of where the debate heads in the next decade, the area of financial services analytics will need to move quickly to stay ahead of advances in technology for smarter auditing, more effective fraud detection and compliance to regulation.